People use pictures to memorialize special memories and convey information visually. An image, such as a painter's canvas or an electronic file, provides a physical or technological foundation for a picture. A picture, on the other hand, represents the visual concept that is discernable to the human eye or mind Thus, images of pictures can be hand-drawn, produced using photography, computer-generated, displayed on a screen, and so forth. Such images are often shared, stored, or manipulated using electronic technology, such as a smart phone or desktop computer. This electronic technology is capable of processing images in many different forms. Two example prominent forms for electronic images are raster images and vector images, each of which has some relative advantages and disadvantages.
For raster images, information is electronically stored on a pixel-by-pixel basis, such as with bitmapped images. The picture of a raster image is divided into a grid of pixels having a known location, and the color of each pixel is stored. A raster image typically has a corresponding native resolution with a fixed width and a height in terms of pixel counts. If an electronic device zooms into the pixels of a raster image, the device can display a zoomed-in image of individual pixels that can be seen by the human eye, which is called pixelation.
For vector images, information is electronically stored for any given vector image based on mathematical formulas, such as lines, curves, and geometric shapes, which can also be filled with color. For example, visually-apparent features of a picture, such as a face or a letter, are represented by different mathematical formulas in a vector image. The mathematical formulas can be manipulated to change the appearance of a vector image. Because a mathematical description has a theoretically infinite resolution, vector images respond well to zooming and resizing.
Typically, many pictures originate as raster images. In many instances, pictures are initially produced in an electronic format using bit-mapped technology, such that the resulting images originate in a raster form. For example, cameras are now ubiquitous due to the proliferation of mobile phones, and cameras produce raster images. Additionally, because some people are more comfortable creating with physical materials or analog tools, art and graphic design projects are often drawn by hand instead of using computer-generated shapes. These hand-drawn images are then electronically scanned as raster images.
However, a vector form of a picture holds certain advantages over a corresponding raster form of the picture. For example, a file size of a vector image can be smaller than that of a corresponding raster image for some pictures, such as those based on design graphics. In other words, vector images are more storage efficient for certain types of pictures. Another advantage of vector images is that vector images are more easily manipulated, and often with better results. For instance, the ability to flexibly resize vector images is greater than that of raster images due to the explicit geometric descriptions of vector images.
For example, if a raster image is up-sampled in an attempt to increase its size, the resulting image becomes grainy as the individual pixels become visible (e.g., due to pixelation). The jagged effects of pixelation can be partially remedied by smoothing (e.g., applying anti-aliasing algorithms), but such smoothing usually results in a blurring of the features of the raster image. Further, if a raster image is down-sampled in an attempt to decrease its size, the resulting image becomes distorted. In contrast, resizing a vector image produces relatively superior results. Being based on mathematical constructs, vector images can be scaled to practically any resolution by redrawing the image at the new size using the mathematical formulas. After either upward or downward scaling, a vector image usually still looks smooth and undistorted.
Consequently, to benefit from the advantages of the vector form, pictures that originate as raster images are often vectorized to produce corresponding vector images. Unfortunately, existing approaches to vectorization produce vector images with a number of different problems. First, noise in an original raster image interferes with vectorization and can cause a cluttered, visually-unsatisfactory vector image to be produced. Second, lines and geometric shapes of the converted vector image may not accurately reflect the visually-apparent features of the original raster image. Third, a vectorization process may fail to properly fill or shade the vector shapes generated for the vector image. Thus, for conversions of raster images to vector images made in accordance with conventional vectorization approaches, these problems collectively cause such conversions to fail to reflect the visually-apparent features of the original picture in manners or to an extent that is desired by the person performing the conversion.